In silico identification of genetic variants in glucocerebrosidase (GBA) gene involved in Gaucher's disease using multiple software tools.

ABSTRACT: Gaucher's disease (GD) is an autosomal recessive disorder caused by the deficiency of glucocerebrosidase, a lysosomal enzyme that catalyses the hydrolysis of the glycolipid glucocerebroside to ceramide and glucose. Polymorphisms in GBA gene have been associated with the development of Gaucher disease. We hypothesize that prediction of SNPs using multiple state of the art software tools will help in increasing the confidence in identification of SNPs involved in GD. Enzyme replacement therapy is the only option for GD. Our goal is to use several state of art SNP algorithms to predict/address harmful SNPs using comparative studies. In this study seven different algorithms (SIFT, MutPred, nsSNP Analyzer, PANTHER, PMUT, PROVEAN, and SNPs&GO) were used to predict the harmful polymorphisms. Amon

SUBMITTER: Manickam M 

PROVIDER: S-EPMC4034330 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature